Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models

ISBN-13: 9780367135591 / Angielski / Twarda / 2021 / 310 str.

Przemyslaw Biecek; Tomasz Burzykowski

Opis

This book is about a new field in statistical machine learning – about interpretation and explanation of predictive models. Machine learning models are widely used in predictive modelling, both for regression and classification.

Spis treści

I. Introduction 1. Introduction. 2. Model Development. 3. Do-it-yourself. 4. Datasets and models. II. Instance Level. 5. Introduction to Instance-level Exploration. 6. Break-down Plots for Additive Attributions. 7. Break-down Plots for Interactions. 8. Shapley Additive Explanations (SHAP) for Average Attributions. 9. Local Interpretable Model-agnostic Explanations (LIME). 10. Ceteris-paribus Profiles. 11. Ceteris-paribus Oscillations. 12. Local-diagnostics Plots. 13. Summary of Instance-level Exploration. III. Dataset Level. 14. Introduction to Dataset-level Exploration. 15. Model-performance Measures. 16. Variable-importance Measures. 17. Partial-dependence Profiles. 18. Local-dependence and Accumulated-dependence Profiles. 19. Residual Diagnostics Plots. 20. Summary of Model-level Exploration. IV. Use-cases. 21. FIFA 19.